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Psy 531 Affects and Emotions
Discussion Guide for March 5
March 5 Perspectives: biological and cognitive
Reading (distributed in class)
Fisher, H. (2000). Lust, attraction, attachment: biology and evolution of three
primary emotion systems for mating, reproduction, and parenting, Journal of
Sex Education & Therapy, 25(1), 96-102.
Johnson, S. (2003). The brain + emotions: Fear. Discover, March, pp. 33-39.
Siemer, M., Mauss, I. & Gross, J.J. (2007). Same situation – different emotions:
how appraisals shape our emotions, Emotion, 7(3), 592-600.
Neumann, R. (2000). The causal influences of attributions on emotions: a
procedural priming approach, Psychological Science, 11(3), 179-182.
Distributed on Feb. 20: informational hand-out on cognitive appraisals
OPTIONALLY DUE: Outline or first draft of “What is an emotion” (first writing
assignment)
Distributions:
Completed course syllabus
Second writing assignment
Citation formatting guide
“Sign-ups” for conference facilitation and book report selections
Data analysis concepts hand-out
Please print out a copy of the Shields article, previously assigned for March 12, now
assigned for March 26. In the copy of the second quarter syllabus I will send to the
library for linking to journal articles, I’ll omit the Shields article to avoid the possibility that
the library will seek copyright clearance on this article twice.
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Our primary tasks will be to consider more deeply two emotions, fear and love, through
a discussion of their biological foundations and of several other emotions (anger,
sadness, guilt & shame) through a discussion of their associated appraisal dimensions.
Comments on the Discover article on fear (2003)
This article is clearly aimed at the “general public.” As such, it contains a number of
potentially misleading simplifications.
One issue, i.e., whether fear-based memories are stored in the amygdala (as suggested
explicitly in the Figure on p. 36 and implied by descriptions of the “low road”) are
acknowledged in the article itself (see description of McGaugh’s work, p. 38). Others,
i.e., the implication that all processing via the “high road” is “conscious and rational”
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(p. 37) are left unchallenged.
Pehaps the best way to undermine the strict “low/high” road dichotomy is to undertake a
brief review of classical conditioning. In the article, a typical example of classical
conditioning is described on p. 35. In this example, the freezing response is an
unconditioned response (UCR) to footshock, which is the unconditioned stimulus (UCS).
After some number of pairings of tone (initially neutral) and shock (UCS), the tone
becomes a conditioned stimulus (CS) that elicits freezing (the conditioned response, or
CR, when it occurs to the tone). For this example, lesions of the amygdala eliminate
both the ability to learn the association between the tone and shock, and also the
conditioned response after the association has been learned. Lesions of the cortex
influence neither.
However, if one changes the paradigm a bit and presents one tone that is paired with
shock (the CS+) and another tone that is not paired with shock (the CS- -- the procedure
is called discriminative classical conditioning), now the cortex is necessary for both the
process of learning and the performance of the CR. Does this mean that discriminative
classical conditioning requires conscious awareness? Evidence suggests that it does
not, but it does apparently require the sensory processing capabilities of the cortex.
The important distinction, therefore, is not between a “low road” from thalamus directly
to amygdala that operates outside of conscious awareness and a “high road” from
thalamus to cortex to amygdala that engages conscious awareness, but rather among a
fast, automatic pathway capable of virtually reflexive responding (the “low road”), a
somewhat slower pathway that engages dedicated sensory processing areas but still
relies on response systems organized by the amygdala, and pathways that engage
higher-level sensorimotor (cortical) processing that can more easily be influenced by
deliberation (and that may be required for all instances of “unlearning” or self-regulation
– we can review what the article has to say about this in class).
Arguably, this (at least) tri-level system of organization provides a useful way of
thinking about the organization of all emotion systems. An obvious thought
question is whether there is an equivalent to the “low road” for all emotions.
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Comments on Fisher (2000)
I don’t have any particular comments to make on this article, though I expect that it will
provoke and tantalize.
One thing to note is the difference between the neuroanatomically-focused approach to
the neural bases of fear described above and the neurochemically-focused approach to
the neural bases of love adopted here. (Flashback: Panksepp.) I append the first page
of Aron et al. (Journal of Neurophysiology, 2005), the fMRI study of activation of the
romantic love system briefly mentioned in this paper. This is a good paper to read if
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you’re interested in how the neurochemical and neuroanatomical approaches can be
brought together. It also has an extensive bibliography that includes both human and
animal studies.
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Comments on Siemer, Mauss & Gross (2007)
This article could provide the empirical backdrop for an entire course on statistics. My
comments are intended to direct your attention to the way these authors set up their
study and to provide some conceptual guidelines to the analytical methods.
1. After reviewing the theoretical motivation for this research project, we should go
over the ways the authors conceptualize the sufficiency and necessity criteria,
which are nicely stated in the paragraph entitled “goals of the present study.”
In studies of the neural bases of particular behaviors, the sufficiency criterion is
established when the activation of (or facilitation of activity in) a neural structure
or neurochemical system causes (in the strong version) or enhances (in the
weaker version) measures of the target behavior. For example, low-level
electrical stimulation of specific areas in the somatotopically-organized motor
cortex causes movements of appropriate contralateral body parts, low-level
electrical stimulation of retintotopically-mapped areas of visual cortex causes
flashes of light in the appropriate part of the visual field, and low-level electrical
stimulation of the lateral hypothalamic area causes satiated animals to eat food.
The necessity criterion is met when the removal or inactivation of a neural
structure or neurochemical system prevents the associated behavior. So a
stroke that involves the motor cortex in the right hemisphere prevents
movements (especially fine-grained movements) of the left arms & legs.
Experimenter-induced damage to the lateral hypothalamic area reduces food
intake of even starving animals.
Direct analogues of these approaches are difficult to implement in studies of
emotion components in humans. Why? We should run through the application
of these approaches to the study of facial expression as a component of emotion,
and then specifically consider the study of appraisal dimensions, both in principle
and as implemented in Siemer et al.
2. Methods: participants. Who were the participants? Were these appropriately
chosen? Were there enough participants? Close reading: the authors state that
there were 122 participants, but there are clear indicators in the paper that the
data from only 108 participants were analyzed. One of these indicators should
be easily found by all, the other requires some knowledge of statistics.
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3. Methods: the emotion induction procedure. The authors clearly wanted to design
an induction procedure with the potential to produce different emotions across
their participants. What do you think of their procedure?
The analysis shown in Table 1 does part of the work of “validating” their
procedure, by showing that several different emotions were rated higher after the
induction than before the induction. When were the “before” ratings taken, and
is this a good procedure for determining a baseline emotional state?
The statistical analyses reported in Table 1 are paired t-tests. The distributed
data analysis concepts hand-out uses an example of a between-groups design
(i.e., the two sets of scores are produced by two different groups of people). This
is a within-subjects analysis, because each participant produced both a “before”
and an “after” score.
The second necessary step in validating the induction procedure is provided in
Figure 1, though the importance of these data in validating the induction
procedure is never explicitly discussed. We’ll go over this Figure in detail in
class, so please spend some time characterizing for yourself the emotion
patterns depicted therein.
4. Methods: the dependent variables. The primary dependent variables in this
study are the ratings of emotion intensity and the ratings of agreement with the
appraisal-relevant statements. We haven’t yet discussed self-report measures
in any detail. What are your intuitions about these?
The patterns of correlations between reported emotion intensities and appraisal
evaluations found in Table 2 provide another stage in the validation of the
methods of this experiment. The authors are careful to say that they are not
testing any particular appraisal theory of emotion (e.g., footnote 2 on p.594). So
what should we be looking for in this Table? Are there any peculiarities that
deserve note?
5. Findings: test of sufficiency. The primary test of sufficiency is found in the
results of the multiple regression, reported in Table 3. Whereas in Table 2 each
set of emotion intensity ratings was correlated separately with each set of
appraisal evaluations, the multiple regression assesses which of the appraisal
ratings, when considered together, best predicts the emotion intensity ratings.
When two different appraisal evaluations are highly correlated with each other, it
is often the case that only one of them will be a significant predictor in the
regression analysis, because the two appraisal evaluations may predict the same
part of the variance in the emotion ratings. Normally, the intercorrelations among
the predictor variables (in this case the appraisal evaluations) will be explicitly
reported – in this case, we have to infer them from the data.
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Overall, there are few, if any, surprises in the regression analysis, i.e., the
findings are similar to those seen in Table 2. The important things to note, then,
are the pattern of appraisals found to be predictive of each emotion, and the
value in the row labeled R2, which tells us how much of the overall variance in
the set of emotion ratings is accounted for by all the appraisal dimensions,
considered together.
6. Findings: test of necessity. This is where the going gets rough statistically, and,
in truth, I can’t evaluate the strength of the evidence. Recall that the question,
stated conceptually, is whether a specific reported emotion response profile can
be identified by the appraisal profile reported by the same person. To make this
analysis approachable, the authors determined whether the emotion profile
assignment of each participant (i.e., which of the 5 profiles discovered by a
hierarchical cluster analysis and depicted in Figure 1) was predicted by (most
closely fit the pattern of) their appraisal evaluations. The authors report that a
48% correct classification rate is very good. Table 4 provides the success rate of
classification by each of the appraisal dimensions.
I am concerned about the possible influence of the unequal number of
participants in each emotion profile, but it’s possible this is taken care of by some
aspect of the statistical procedure. I do find inspection of Figure 2 to be
interesting and can make it “fit” with the p-values in Table 4, so I think I can lead
us through a semi-serious discussion of these findings.
Bottom lines. I think the paper is most useful as:
1. An example of the strengths and weaknesses of a relatively strong laboratorybased emotion induction procedure
2. An example of the difficulties associated with self-reports of emotion experience
and of appraisals
3. A good stimulus for thinking about different emotional states and the strengths
and weaknesses of appraisal theories
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Comments on Neumann (2000)
In my view (shared, apparently, by Siemer et al.), this is one of the most important
papers to be published as a test of appraisal theory. It is relatively straightforward
compared to Siemer et al. Some things to track:
1. The way in which appraisal tendencies were manipulated, and the results of the
validation of this procedure (the “manipulation check”)
2. The emotion induction procedure
3. The use of multiple dependent variables (self-report and observational)
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4. The appropriate use of a MANOVA (multivariate analysis of variance) in which it
is recognized that the ratings of anger and the ratings of guilt are likely to be
correlated (in this case, negatively correlated). A proper (but less powerful)
alternative is to analyze the effect of the independent variable (priming condition)
on the guilt ratings and on the anger ratings separately. The improper alternative
is to treat the type of rating as an independent variable in a univariate ANOVA,
ignoring the fact that the two rating types are not independent of one another
(i.e., as one goes up, the other will probably go down for reasons beyond the
influence of the independent variable).
5. The path/mediational analysis, which provides a strong test of the sufficiency
criterion.
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Suggested reading
See Guide for April 27 for further references regarding individual emotions, and the
suggested readings listed in the informational hand-out on appraisal theories.
A few recommendations re: the biology of fear conditioning:
LeDoux, J. E. & Phelps, E.A. (2000). Emotion networks in the brain, Chapt 10 in
Handbook of Emotions, 2nd ed. (LR).
McGaugh, J.L. (2004). The amygdala modulates the consolidation of memories of
emotionally arousing experiences, Annual Review of Neuroscience, 27, 1-28.
Ohman, A. & Mineka, S. (2001). Fears, phobias, and preparedness: toward an
evolved module of fear and fear learning, Psychological Review, 108(3), 483522.
Phelps, E. A. (2004). Human emotion and memory: interactions of the amygdala
and hippocampal complex. Current Opinion in Neurobiology, 14, 198-202.
Re: appraisal theories, I’d especially like to recommend the two highly recommended
readings listed in the syllabus for March 5:
Ellsworth, P. & Scherer, K. (2002). Appraisal processes in emotion, In Davidson, R.J.,
Scherer, K. & Goldsmith, H. (2002). Handbook of Affective Sciences, Oxford
University Press, pp. 572-595. (LR, and one copy in Psych Lounge)
Siemer, M. & Reisenzein, R. (2007). The process of emotion inference, Emotion, 7(1),
1-20 and following commentary. A debate between appraisal-based and relational
interpretations of a set of findings.
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